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   "source": [
    "# Chapter 04: Conservation laws\n",
    "# *Fluid theory*"
   ]
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   "source": [
    "Once collisions are numerous enough to average particle motion to that of a fluid, we can use a simpler model. This model is now using macroscopic quantities like the mass density $\\rho$ $(kg/m^3)$, the velocity $\\vec v$ $(m/s)$ or the kinetic energy density $\\rho v^2$ $(J/m^3)$."
   ]
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   "source": [
    "## Kinetic theory\n",
    "### The distribution function\n",
    "As we saw in the previous chapter, the best way to define collisions is to use particles which are labeled using invariant quantities of motion (rest mass $m$ and charge $q$) as well as quantities that varies with motion (the position $\\vec r$ and the velocity $\\vec v$)."
   ]
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     "slide_type": "fragment"
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   "source": [
    "If we are at a fix position is space $\\vec r=(x,y,z)$ we can count all the particles inside an infinitely small small volume $dV=dxdydz$. Let's say that this number is $dN$.  Once all these particles have been counted we can sort them as a function of their velocities. We end up with a distribution of particles across all available velocities at the location $\\vec r$. Now, this distribution $f$ is a function of both $\\vec r$ and $\\vec v$ and we can write it as $f(\\vec r,\\vec v,t)$. $f$ is simply the number or particles per $m^3$ and $(m/s)^3$."
   ]
  },
  {
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   "metadata": {
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   "source": [
    "One can use the momentum $\\vec p=m\\vec v$ instead and then $f$ is now function of both $\\vec r$ and $\\vec p$.\n",
    "$$f=f(x,y,z,p_x,p_y,p_z,t)$$\n",
    "So $f$ has a total of six coordinates plus time. To differentiate between the two different spaces (space and momentum space) the distribution function is said to be a function of space $(x,y,z)$ and phase space $(p_x,p_y,p_z)$. "
   ]
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   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "subslide"
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   "source": [
    "### Boltzmann equation\n",
    "For a closed system with no source or sink of:\n",
    "1. particles (i.e. mass conservation)\n",
    "2. momentum (i.e. momentum conservation)\n",
    "3. energy (i.e. energy conservation)\n",
    "\n",
    "we have $$df(\\vec r,\\vec p,t)=0\\tag{4.1}$$\n",
    "\n",
    "Note that Eq. $(4.1)$ is a total derivative since both $\\vec r$ and $\\vec p$ are both function of time. Evidently, we can use the chain rule to get\n",
    "$$df(\\vec r,\\vec p,t)=\\frac{\\partial f}{\\partial t}dt+\\frac{\\partial f}{\\partial \\vec r}d\\vec r+\\frac{\\partial f}{\\partial \\vec p}d\\vec p$$"
   ]
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   "source": [
    "Clearly, we can rewrite this equation using the fact that \n",
    "$$\\frac{\\partial f}{\\partial \\vec r}d\\vec r=\\frac{\\partial f}{\\partial x}dx+\\frac{\\partial f}{\\partial y}dy+\\frac{\\partial f}{\\partial z}dz=\\vec \\nabla_{\\vec r}\\,f.d\\vec r\\tag{4.2}$$ and \n",
    "$$\\frac{\\partial f}{\\partial \\vec p}d\\vec p=\\frac{\\partial f}{\\partial p_x}dp_x+\\frac{\\partial f}{\\partial p_y}dp_y+\\frac{\\partial f}{\\partial p_z}dp_z=\\vec \\nabla_{\\vec p}\\,f.d\\vec p\\tag{4.3}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "So we are left with $$\\frac{\\partial f}{\\partial t}dt+\\vec \\nabla_{\\vec r}\\,f.d\\vec r+\\vec \\nabla_{\\vec p}\\,f.d\\vec p=0$$\n",
    "Clearly, we can divide by $dt$ and use the fact that $$\\frac{d\\vec p}{dt}=\\vec F$$ to get $$\\frac{\\partial f}{\\partial t}+\\frac{\\vec p}{m}. \\vec \\nabla_{\\vec r}\\,f+\\frac{\\vec F}{m}.\\vec \\nabla_{\\vec v}\\,f=0\\tag{4.4}$$"
   ]
  },
  {
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   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
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   "source": [
    "Note that, besides using $d\\vec p/dt=\\vec F$, there is no physics added to Eq. $(4.4)$. It's all math! From now on, we are going to use velocity phase space coordinate $\\vec v$ instead of momentum phase space coordinate $\\vec p$, so eq. $(4.4)$ becomes\n",
    "$$\\frac{\\partial f}{\\partial t}+\\vec v. \\vec \\nabla_{\\vec r}\\,f+\\frac{\\vec F}{m}.\\vec \\nabla_{\\vec v}\\,f=0\\tag{4.4}$$"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "So when does the physics comes into play? During interaction between particles, a.k.a. collisions. These collisions are source or sink of particles. For instance, consider collisions that push particles from a velocity $\\vec v_1$ to a velocity $\\vec v_2$, then $f(\\vec r,\\vec v_1,t)$ decreases with time while $f(\\vec r,\\vec v_2,t)$ increases with time. For now, we encapsulate collisions inside a symbolic function $$\\Big(\\frac{\\partial f}{\\partial t}\\Big)_{coll}$$ and we get,\n",
    "$$\\frac{\\partial f}{\\partial t}+\\vec v. \\vec \\nabla_{\\vec r}\\,f+\\frac{\\vec F}{m}.\\vec \\nabla_{\\vec v}\\,f=\\Big(\\frac{\\partial f}{\\partial t}\\Big)_{coll}$$\n",
    "Since $\\vec F/m=\\vec a$ we get the final equation, known as Boltzmann equation,\n",
    "$$\\frac{\\partial f}{\\partial t}+\\vec v. \\vec \\nabla_{\\vec r}\\,f+\\vec a.\\vec \\nabla_{\\vec v}\\,f=\\Big(\\frac{\\partial f}{\\partial t}\\Big)_{coll}\\tag{4.5}.$$"
   ]
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "![image.png](attachment:image.png)\n",
    "**Fig.1 Change of f as a function of time inside the volume dV due to a spacial variation of f along the x axis and a velocity parallel to that gradient.**\n",
    "\n",
    "The figure above shows that $f$ changes in time due to a change in f along the x-direction and a velocity $v_x$ that moves this change insdie the volume dV."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Vlasov equation\n",
    "Vlasov realized that to properly capture Coulomb collisions, one should not use the collision operator $(\\frac{\\partial f}{\\partial t})_{coll}$ but split the charge particle distribution function into two distribution functions:\n",
    "1. one for the electrons, $f_e$\n",
    "2. one for the ions, $f_i$\n",
    "\n",
    "We suppose here that there is only one ions species with ionization $Z_i$. However, if other collisions (e.g. charged particles-neutrals) are not negligible then they have to be taken into account."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The total system used by Vlasov let the two distribution functions interact via the electric and magnetic fields that these particles generate. \n",
    "$$\\begin{split}\n",
    "\\frac{\\partial f_e}{\\partial t} + \\vec v.\\vec \\nabla_{\\vec r}\\, f_e - \\frac{e}{m_e}\\left(\\vec {E}+\\vec v\\times\\vec {B}\\right).\\vec \\nabla_{\\vec v}\\,f_e = 0 \\\\ \n",
    "\\frac{\\partial f_i}{\\partial t} + \\vec v.\\vec \\nabla_{\\vec r}\\,f_i +\\frac{ Z_i e}{m_i}\\left(\\vec E+\\vec v\\times\\vec B\\right).\\vec \\nabla_{\\vec v}\\,f_i  = 0 \\end{split}\n",
    " \\tag{4.6}\n",
    "$$ \n",
    "So how do we find these global fields?\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We used Maxwell's equations $$\n",
    "\\begin{split}\n",
    "\\vec \\nabla\\times\\vec {B} =\\mu_0\\vec {j}+\\mu_0\\varepsilon_0 \\frac{\\partial\\vec {E}}{\\partial t} \\\\\n",
    "\\vec \\nabla\\times\\vec {E} =-\\frac{\\partial\\vec {B}}{\\partial t} \\\\\n",
    "\\vec \\nabla\\cdot\\vec {E}  =\\frac{\\rho_E}{\\varepsilon_0} \\\\\n",
    "\\vec \\nabla\\cdot\\vec {B}  =0\n",
    "\\end{split} \n",
    " \\tag{4.7}$$\n",
    "By *global*, Vlasov meant that these fields are the fields created by all the particles at the location $(x,y,z)$ but average over all the particle momenta at this location."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The global fields are defined by the charge density $\\rho_E(x,y,z)$ and by the electrical current $\\vec j(x,y,z)$. Note that these quantities are now independent of the particle momenta. Indeed, this feat is only possible by using \n",
    "$$\\rho_E=e\\int(Z_i f_i-f_e)d^3v \\\\\n",
    "\\vec j=e\\int(Z_i f_i \\vec v -f_e \\vec v)d^3v $$\n",
    "Basically, we integrated the distribution function over all velocities at each location $(x,y,z)$ to get local quantities where the velocity information has been encapsulated. This approach reduces the amount of information we have to deal with."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Moment equations\n",
    "What do we obtain if we integrate the distribution function $f_i$ or $f_e$ over all velocities? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We obtain the number density in $particles/m^3$\n",
    "$$n_{i,e}=\\int f_{i,e}(x,y,z,v_x,v_y,v_z,t)d^3v\\tag{4.8}$$\n",
    "Note that we used the subscript $i$ and $e$ in the same equations rather than writing one equation for the electrons and one for the ions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "What happens if the integrate the flux of the distribution function $\\vec \\Gamma_{f_{i,e}}=f_{i,e}\\vec v$ over all velocities ?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We obtain the total flux of particles $\\vec \\Gamma_{i,e}$\n",
    "$$\\vec \\Gamma_{i,e}=\\int f_{i,e}(x,y,z,v_x,v_y,v_z,t)\\vec v d^3v$$\n",
    "Since we have defined the flux as a number density times a velocity, then we can get a flow velocity $\\vec u_{i,e}$ from dividing the flux by the particle density $n_{i,e}$\n",
    "$$\\vec u_{i,e}=\\frac{\\vec \\Gamma_{i,e}}{n_{i,e}}$$\n",
    "which we can rewrite as\n",
    "$$n_{i,e}\\vec u_{i,e}=\\int f_{i,e}(x,y,z,v_x,v_y,v_z,t)\\vec v d^3v\\tag{4.9}$$\n",
    "Note that the flow velocity $\\vec u$ is different for ions and electrons, while the velocity $\\vec v$ is a phase space coordinate of the distribution function, like $\\vec x$ is a spacial coordinate. So if $\\vec x$ has no subscripts, then $\\vec v$ should not either!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "What is the physical meaning of $m_{i,e}n_{i,e}v^2$?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "This is the kinetic energy density. What happens if we multiply the distribution function by $\\vec v^2/2$?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We get the density of kinetic energy $\\epsilon_{i,e}$ (not to confuse with $\\varepsilon$ which is the permitivity of materials).\n",
    "$$\\epsilon_{i,e}=\\int f_{i,e}(x,y,z,v_x,v_y,v_z,t)\\frac{\\vec v^2}{2} d^3v\\tag{4.10}$$\n",
    "This energy density of the fluid is made up of energy at the macroscopic scale (i.e. kinetic energy) and energy at the miscroscopic scale, i.e. magnetic energy and internal energy. In our case, internal energy is simply pressure. \n",
    "$$m_{i,e}\\epsilon_{i,e}=\\frac{1}{2}m_{i,e}n_{i,e}\\vec u_{i,e}^2+\\frac{3}{2}p_{i,e}$$\n",
    "Since $\\epsilon_{i,e}$, $n_{i,e}$ and $\\vec u_{i,e}$ are know from the previous moment equations, we can define the pressure as\n",
    "$$\\frac{3}{2}p_{i,e}=m_{i,e}\\epsilon_{i,e}-\\frac{1}{2}m_{i,e}n_{i,e}\\vec u_{i,e}^2$$\n",
    "Here $p_{i,e}(\\vec r,t)$ is the isotropic pressure. Note that $\\frac{3}{2}p_{i,e}$ corresponds to the internal (i.e. microscopic) energy density, while $\\frac{1}{2}m_{i,e}n_{i,e}\\vec u_{i,e}^2$ correspond to the flow kinetic energy density. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Let's compute numerically the particle density for the distribution function given by\n",
    "$$f(\\vec r,\\vec v,t)=A_0\\exp\\Big(-\\sqrt{\\frac{x^2+y^2+z^2}{L_0^2}}\\Big)\\exp\\Big(-\\frac{v_x^2+v_y^2+v_z^2}{v_0^2}\\Big)$$\n",
    "where $A_0=1000\\,particles/m^6s^3$, $L_0=1\\mu m$ and $v_0=0.1\\,m/s$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3/dist-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.17.3 and <1.25.0 is required for this version of SciPy (detected version 1.26.4\n",
      "  warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the value is 5.568327996831708 particles/m^3 with error 2.0286622419933955e-08\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from scipy.integrate import nquad\n",
    "from math import exp as exp\n",
    "def integrand(vx,vy,vz,A0,v0):\n",
    "    return A0*exp(-(vx**2+vy**2+vz**2)/v0**2)\n",
    "I = nquad(integrand,[[-np.inf,np.inf],[-np.inf,np.inf],[-np.inf,np.inf]], args=(1e3,.1))\n",
    "print('the value is',I[0],'particles/m^3 with error',I[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "So the answer is $n(x,y,z)=5.568327996831708\\exp\\Big(-\\sqrt{\\frac{x^2+y^2+z^2}{L_0^2}}\\Big)\\,particles/m^3$. Can we compute the previous integral analytically? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Yes. The integral of $\\exp(-x^2)$ from $-\\infty$ to $+\\infty$ is"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$\\int_{-\\infty}^{+\\infty}\\exp(-x^2)dx=\\sqrt{\\pi}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Since we know that $$\\int\\int\\int_{-\\infty}^{+\\infty}\\exp\\Big(-\\frac{v_x^2+v_y^2+v_z^2}{v_0^2}\\Big)dv_xdv_ydv_z=\\Big(\\int_{-\\infty}^{+\\infty}\\exp(-\\frac{v_x^2}{v_0^2})dv_x\\Big)^3$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "we get $$\\int\\int\\int_{-\\infty}^{+\\infty}\\exp\\Big(-\\frac{v_x^2+v_y^2+v_z^2}{v_0^2}\\Big)=(v_0\\sqrt{\\pi})^3$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "So the answer is $n(x,y,z)=A_0(v_0\\sqrt{\\pi})^3\\exp\\Big(-\\sqrt{\\frac{x^2+y^2+z^2}{L_0^2}}\\Big)\\,particles/m^3$. The particles have a Gaussian distribution."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Two fluid magnetohydynamics\n",
    "Now that we have integrated $f$, $f\\vec v$ and $f\\vec v^2$ over all possible velocities, let's redo the same thing with $df$, $df\\vec v$ and $df \\vec v^2$.  \n",
    "### Conservation of mass\n",
    "The conservation of mass in obtained by integrating Vlasov's equation\n",
    "$$\\int\\int\\int_{-\\infty}^{+\\infty}\\frac{\\partial f_e}{\\partial t} + \\vec v.\\vec \\nabla_{\\vec r}\\, f_e +\\vec a.\\vec \\nabla_{\\vec v}\\,f_ed^3v=\\int\\int\\int_{-\\infty}^{+\\infty}\\Big(\\frac{\\partial f}{\\partial t}\\Big)_{e\\,coll}d^3v\\tag{4.11}$$\n",
    "Since the left hand side of Eq. $(4.11)$ is integrated for all possible velocities, we will get the same results for electrons and ions. However, the right hand side of Eq. $(4.11)$ is dependent on cross-sections and has to be treated separately for ions and electrons."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "When we integrate eq. $(4.11)$ over all velocities, we find the first conservation equation, called the conservation of mass or *continuity equation*\n",
    "$$\\frac{\\partial n_e}{\\partial t}+\\vec \\nabla . \\big(n_e\\vec u_e\\big)=S_e\\tag{4.12}$$\n",
    "$S_e$ is the sources of particles in this equations and comes from\n",
    "$$S_e=\\int\\int\\int_{-\\infty}^{+\\infty}\\Big(\\frac{\\partial f}{\\partial t}\\Big)_{e\\,coll}d^3v$$\n",
    "Note that these collisions are all but Coulomb collisions in the context set by Vlasov. If $S_e$ is positive then the electron density $n_e$ at the location $(x,y,z)$ is increasing *or* the flux of particle leaving this location is non-zero and points away from this volume. This is the meaning of the divergence operator $\\vec\\nabla.\\bullet$ \n",
    "\n",
    "Physically, what can be considered a source of electrons at a given location?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Ionizations.\n",
    "\n",
    "Note that injecting electrons at this location does not count because the represent an electron flux and this would be accounted for in $\\vec \\nabla . \\big(n_e\\vec u_e\\big)$. When $S_e$ is negative then there is a sink of electrons. Physically, what can be considered a sink of electrons at a given location?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Recombinations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "It is usual to break $S_e$ down into two **positive** quantities, $G_e$, the term corresponding to electron sources or *gains*, and $L_e$, the term corresponding to electrons sinks or *losses*. So, we get \n",
    "$$\\frac{\\partial n_e}{\\partial t}+\\vec \\nabla . \\big(n_e\\vec u_e\\big)=G_e-L_e.\\tag{4.13}$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "One way to understand conservation of mass (with no subscripts) $\\frac{\\partial n}{\\partial t}+\\vec \\nabla . \\big(n\\vec u\\big)=0$ is to look at Fig. 1 and replace $f$ with $n$. If $n$ changes along one spacial direction and there is also a velocity along this direction then $n$ changes with time. In other words, $n\\vec v$ represents a flux of particles. If this  flux of particles is forced inside a volume, then the number of particles inside that volume increases with time, i.e. $\\frac{\\partial n}{\\partial t}$ is positive.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Clearly, we can repeat the whole process for ions\n",
    "$$\\frac{\\partial n_i}{\\partial t}+\\vec \\nabla . \\big(n_i\\vec u_i\\big)=G_i-L_i.\\tag{4.14}$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "And we can also apply this method when particles are neutrals (i.e. gas) and we get\n",
    "$$\\frac{\\partial n_g}{\\partial t}+\\vec \\nabla . \\big(n_g\\vec u_g\\big)=G_g-L_g\\tag{4.15}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "If we look at ionizations only, we can write $$G_e=\\nu_{iz}n_e$$\n",
    "or \n",
    "$$G_e=n_en_g\\sigma<v>_{ionization}$$\n",
    "Note that $G_e=L_g$, $G_e=G_i$, together with $G_g=0$ (no recombinations) and $L_g=G_i$. This effectively couples all three equations together.\n",
    "\n",
    "If ions can be ionized multiple times, then we will have a conservation equation for each charged ion species (e.g. single ionized, double ionized, ...). But all the conservation equations are still coupled via their source terms."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Conservation of momentum\n",
    "We now look at what happens when Vlasov equations for ions and electrons are multiplied by $m_{i,e}\\vec v$. Integrating over all velocities we get conservation of momentum. \n",
    "$$\\frac{\\partial n_e\\vec u_e}{\\partial t}+\\vec \\nabla \\cdot (n_e\\vec u_e \\vec u_e)=\\frac{1}{m_e}\\big(-en_e[\\vec E +\\vec u_e \\times \\vec B]-\\vec \\nabla p_e+\\vec F|_{e\\,coll}\\big)$$\n",
    "and \n",
    "$$\\frac{\\partial n_i\\vec u_i}{\\partial t}+\\vec \\nabla \\cdot (n_i\\vec u_i \\vec u_i)=\\frac{1}{m_i}\\big(Z_ien_i[\\vec E +\\vec u_i \\times \\vec B]-\\vec \\nabla p_i+\\vec F|_{i\\,coll}\\big)$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Here by $\\vec u\\vec v$ we mean the outer product (i.e. vector product not dot product) which is a matrix\n",
    "$$\\begin{align}\\vec u\\vec v = \n",
    "\\begin{bmatrix}u_x \\\\ u_y \\\\ u_z \\end{bmatrix}\n",
    "\\begin{bmatrix}v_x & v_y & v_z\\end{bmatrix}\n",
    "= \\begin{bmatrix}u_xv_x & u_xv_y & u_xv_z \\\\ u_yv_x & u_yv_y & u_yv_z \\\\ u_zv_x & u_zv_y & u_zv_z \\end{bmatrix}.\\end{align}$$\n",
    "Note that $\\vec \\nabla \\cdot \\big(\\vec u \\vec v\\big )$ is now a vector!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "While the momentum equation seems more complex than mass conservation, it is in fact the same equation but where $n$ as been replaced by $n\\vec u$. So one can see $mn\\vec u \\vec u$ is the flux of momentum $mn\\vec u$ traversing a surface with velocity $\\vec u$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The operator vector $\\vec F|_{coll}$ represents the force density of collisions with respect to other ions or neutrals. We will ignore such effects here. Further, we also dropped in this treatment secondary effects, such as viscosity. In this context, the pressure is given by our integral calculus and has the following form.\n",
    "$$p_{i,e}= \\frac{1}{3}m_{i,e}n_{i,e}\\Big<\\big(v_{i,e}-u_{i,e}\\big)^2\\Big>_{\\vec v}$$\n",
    "where $\\Big<\\big(\\bullet\\big)^2\\Big>_{\\vec v}$ is the average operator over all velocities.\n",
    "\n",
    "If we now suppose that the electron and ion plasmas behave like an ideal gas then this operator yields for both pressures, $p_e=n_eeT_e$ and $p_i=Z_in_ieT_i$. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In summary, we get conservation laws for momentum\n",
    "$$\\frac{\\partial n_e\\vec u_e}{\\partial t}+\\vec \\nabla \\cdot (n_e\\vec u_e \\vec u_e)=\\frac{1}{m_e}\\big(-en_e\\vec E +\\vec j_e \\times \\vec B-\\vec \\nabla p_e\\big)\\tag{4.16}$$\n",
    "and \n",
    "$$\\frac{\\partial n_i\\vec u_i}{\\partial t}+\\vec \\nabla \\cdot (n_i\\vec u_i \\vec u_i)=\\frac{1}{m_i}\\big(Z_ien_i\\vec E +\\vec j_i \\times \\vec B-\\vec \\nabla p_i\\big)\\tag{4.17}$$\n",
    "after ignoring collisions and using the fact that $qn_q\\vec u_q=\\vec j_q$, the current density for the particle with charge q."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Conservation of energy\n",
    "We now look at what happens when Vlasov equations for ions and electrons are multiplied by $m_{i,e}v^2$ and then integrated over all velocities. This gives conservation of energy for both species. \n",
    "$$\\frac{\\partial \\epsilon_e}{\\partial t}+\\vec \\nabla \\cdot (\\epsilon_e\\vec u_e)=\\frac{1}{m_e}\\big(-\\vec \\nabla \\cdot Q_e+\\vec j_e.\\vec E\\big)\\tag{4.18}$$\n",
    "Clearly, we have here a similar structure in the equation, mainly a change in time od a certain quantity $\\sigma$ is related to its flux $\\sigma \\vec u$ via the divergence operator $\\vec \\nabla$. And as before we have introduced a new quantity $\\vec Q_e$ that is the flux of energy at the microscopic scale, i.e. $\\frac{1}{2}m_en_e<u_e^2\\vec u_e>_e$, also called heat flux. The energy density source term $\\vec j_e.\\vec E$ is the work of the electric field on the moving electrons."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We see here that we were not able to define $\\vec Q_e$ from any previous quantities. So we will need to come up with a model for this effect, purely caused by collisions. An popular approximation for the heat flux is\n",
    "$$\\vec Q_e=\\kappa_e\\vec \\nabla T_e\\tag{4.19}$$\n",
    "where $\\kappa_e$ is the electron heat conductivity."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Of course, we get a similar equations for the ions\n",
    "$$\\frac{\\partial \\epsilon_i}{\\partial t}+\\vec \\nabla \\cdot (\\epsilon_i\\vec u_i)=\\frac{1}{m_i}\\big(-\\vec \\nabla \\cdot Q_i+\\vec j_i.\\vec E\\big)\\tag{4.19}$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Summary\n",
    "For any fluid, ions or electrons, we have shown that an explicit change in time of any moment ($n$, $n\\vec u$ or $\\epsilon$) can only be cause by an explicit change of flux in space ($n\\vec u$, $n\\vec u \\vec u$ or $\\epsilon \\vec u$) or by explicit cources and sinks. Sources and sinks comes from collisions or from electromagnetic sources (according to Vlasov theory).\n",
    "\n",
    "The physical meaning of the moments on the left hand side of every equation is tightly bound to the integral operator, but the moments and their flux can alsways be defined as long as an integral operator can be defined. This is not true for most terms on the right hand side. If they come from collision operators, the collision operators have to be defined physically (non trivial task when dealing with plasmas) and some quantities have to be purely and simply defined: the closure quantities  (like $p$ or $\\vec Q$).\n",
    "\n",
    "$$\\begin{align}\n",
    "&\\frac{\\partial n_e}{\\partial t}+\\vec \\nabla . \\big(n_e\\vec u_e\\big)=0\\\\\n",
    "&\\frac{\\partial n_i}{\\partial t}+\\vec \\nabla . \\big(n_i\\vec u_i\\big)=0\\\\\n",
    "&\\frac{\\partial n_e\\vec u_e}{\\partial t}+\\vec \\nabla \\cdot (n_e\\vec u_e \\vec u_e)=\\frac{1}{m_e}\\big(-en_e\\vec E +\\vec j_e \\times \\vec B-\\vec \\nabla p_e\\big)\\\\\n",
    "&\\frac{\\partial n_i\\vec u_i}{\\partial t}+\\vec \\nabla \\cdot (n_i\\vec u_i \\vec u_i)=\\frac{1}{m_i}\\big(Z_ien_i\\vec E +\\vec j_i \\times \\vec B-\\vec \\nabla p_i\\big)\\\\\n",
    "&\\frac{\\partial \\epsilon_e}{\\partial t}+\\vec \\nabla \\cdot (\\epsilon_e\\vec u_e)=\\frac{1}{m_e}\\big(-\\vec \\nabla \\cdot Q_e+\\vec j_e.\\vec E\\big)\\\\\n",
    "&\\frac{\\partial \\epsilon_i}{\\partial t}+\\vec \\nabla \\cdot (\\epsilon_i\\vec u_i)=\\frac{1}{m_i}\\big(-\\vec \\nabla \\cdot Q_i+\\vec j_i.\\vec E\\big)\\\\\n",
    "&\\vec \\nabla\\times\\vec {B} =\\mu_0\\vec {j}+\\mu_0\\varepsilon_0 \\frac{\\partial\\vec {E}}{\\partial t} \\\\\n",
    "&\\vec \\nabla\\times\\vec {E} =-\\frac{\\partial\\vec {B}}{\\partial t} \\\\\n",
    "&\\vec \\nabla\\cdot\\vec {E}  =\\frac{\\rho_E}{\\varepsilon_0} \\\\\n",
    "&\\vec \\nabla\\cdot\\vec {B}  =0\\\\\n",
    "\\end{align}$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Conservation equations for a single fluid\n",
    "The major difficulty in going from two fluid equations to equations for one single fluid is the disparity of both temporal and spacial scales between the ions and the electrons. Because they have the same charge, share similar momentum source or sink, but because the electrons are so much lighter, they react more quickly, 2000 times more quickly if we compare protons and electrons. As a results, two-fluid equations have to be solved on the electron time scale, requiring a numerical treatment that calls for very small time steps.\n",
    "\n",
    "Because the bulk of the mass lies with the ion fluid, macroscopic effects are most visible at the ion scale. Yet the equations have to be solved very slowly, to account for electron physics, and their interactions with the ions. \n",
    "\n",
    "To simplify the problem, we assume macroscopic ambipolarity ($\\vec u_i\\approx\\vec u_e$) and quasi-neutrality ($n_e\\approx Z_in_i$). We use here the symbol $\\approx$ (i.e. almost equal) allows for the existance of an electrical current density $\\vec j=Z_ie\\vec u_i-en_e\\vec u_e$, which can be seen as a difference in flow velocity between ions and electrons. Perfect neutrality and ambipolarity forces the electrical current to be $\\vec j=\\vec 0$.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Because of these two assumptions, we can redefine our electron distribution function so it takes into account many time cycles on the electron scale inside volumes compatible with the ion scale length. By doing so, we virtually have not change the left hand side of Eqs. $(4.13)$, $(4.16)$ and $(4.18)$. We have put the mathematical burden on the right hand side, i.e. on the closure quantities (e.g. $p$ or $\\vec Q$ )and the collision operators. Assumptions will be made on these quantities latter. In this case, we can rewrite all our moments as\n",
    "$$\\begin{align}\n",
    "&n=\\sum_{i,e}n_{i,e}\\\\\n",
    "&\\rho=\\sum_{i,e}n_{i,e}m_{i,e}\\\\\n",
    "&m=\\sum_{i,e}m_{i,e}\\\\\n",
    "&n\\vec u=\\frac{1}{\\rho}\\sum_{i,e}\\rho_{i,e}u_{i,e}\\\\\n",
    "&\\vec j=Z_ien_i\\vec u_i-en_e\\vec u_e\\end{align}$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "One way to keep as much electron physics as possible without *breaking the bank* is to look at the impact of the electrons on the electric and magnetic fields felt by the ions. This is called Ohm's law."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Ohm's law\n",
    "Ohm's law (or the generalized Ohm's law as we are going to study it) is simply that. It is a law that averages over electron motion at the microscopic (fast) scale to give the effective electric field felt by the ion at the macroscopic (ion) scale. \n",
    "\n",
    "One might think that quasi-neutrality means that there is no electric field inside a plasma. In fact, it states that there is no **source** of electrostatic field inside a plasma, i.e. $\\rho_E=Z_ien_i-en_e=0$. However, this is not because $\\vec \\nabla\\cdot\\vec E=0$ that there is no electrostatic field. It just means there exist a vector $\\vec A_E$ such that $\\vec E=\\vec \\nabla\\times\\vec A_E.$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The simplest case is coming from electron collisions with the ions inside materials. When averaged over many collisions, the force experience collectively by the electron is some kind of drag (fluid view). This is called resistivity in physics. If there is no external electric field, thermal motion averages out to zero. If there is an external electric field, then there is net motion in the direction of the field. But this flow is not proportional to the average force $<-e\\vec E>$. This is because the ion are deflecting more eletrons than the electric field can entrain the electrons. As a result, the flow is reduced and depends on the lectric field *and* the type of material via the factor of proportionality $\\eta$, called resistivity\n",
    "$$\\vec E=\\eta \\vec J$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Ohm was inspired by Fourier's work on heat conduction (thermodynamics or statistical approach) and use experimental measurements to deduce the linear correspondance between field and current.  While $\\vec j$ is a consequence of the electric field in this framework, the reverse is also true. A flowing current (generated by gravity for instance) can generate an eelctric field."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "More generally, electric fields can be generated by different phenemona tightely connected to electron physics. We will look at the following in the next chapter:\n",
    "1. Dynamo\n",
    "2. Hall effect\n",
    "3. Electron pressure (also known as the Biermann battery term)\n",
    "4. Electron inertia"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Conservation laws\n",
    "While the meaning of electron closure quantities and collisional operators can be recast on the ion time scale, their mathematical definitions become very restrictive. We lose a sizable portion of electron physics by doing so. If the physical system indeed allows it, then the equations will closely match the physical behavior of this system. If not, then it will be a poor approximation. Using the one-fluid quantities as defined above, we get\n",
    "$$\\begin{align}\n",
    "&\\frac{\\partial n}{\\partial t}+\\vec \\nabla . \\big(n\\vec u\\big)=0\\tag{4.20}\\\\\n",
    "&\\frac{\\partial n\\vec u}{\\partial t}+\\vec \\nabla . \\big(n\\vec u\\vec u\\big)=\\frac{1}{m}(\\vec j\\times\\vec B-\\vec\\nabla\\cdot p)\\tag{4.21}\\\\\n",
    "&\\frac{\\partial \\epsilon}{\\partial t}+\\vec \\nabla \\cdot (\\epsilon\\vec u)=\\frac{1}{m}\\big(-\\vec \\nabla \\cdot Q+\\eta j^2\\big)\\tag{4.22}\n",
    "\\end{align}$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Note that the electric field has been completely eliminated from these equations, by using Ohm's law ($\\vec E=\\eta \\vec j$). Further, when ignoring electromagnetic radiations ($\\varepsilon_0\\mu_0\\frac{\\partial \\vec E}{\\partial t}\\approx \\vec 0$), it can be dropped from Maxwell's equations $(4.7)$ yielding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$\\begin{align}\n",
    "&\\frac{\\partial\\vec {B}}{\\partial t}=-\\vec \\nabla\\times\\big( {\\frac{\\eta}{\\mu_0}}\\vec \\nabla\\times\\vec {B}\\big) \\tag{4.23}\\\\\n",
    "&\\vec \\nabla\\cdot\\vec {B}=0 \\tag{4.24}\n",
    "\\end{align} \n",
    "$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Hydrodynamics\n",
    "\n",
    "Before solving flows where electromagnetism plays an important role, let's first look at what happens when flows are solely driven by kinetic energy, i.e. $B=0$ and $E=0$. In this case, we need to solve Eqs. $(4.20)$ to $(4.22)$ with $\\vec j\\times \\vec B=\\vec 0$. We will suppose also that all the heat is transferred via convection rather than conduction so we also ignore $\\vec Q$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### Finite volume\n",
    "To do this we recast our conservation laws using a more general framework. Regardless of their sources (even if fields are involved), Eqs. $(4.20)$ to $(4.22)$ can be written as\n",
    "$$\\frac{\\partial U}{\\partial t}+\\vec \\nabla \\cdot \\vec F(U)=S_U\\tag{4.25}$$\n",
    "Here $U$ can be a scalar or a vector. If we discritize our domain into an ensemble of adjacent domains $\\Omega_j$ with boundary $\\partial\\Omega_j$ we can rewrite Eq. $(4.25)$ as\n",
    "$$\\iiint_{\\Omega_j}\\frac{\\partial U}{\\partial t}dV+\\iiint_{\\Omega_j}\\vec \\nabla \\cdot \\vec F(U)dV=\\iiint_{\\Omega_j}S_U\\,dV$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Using Gauss's theorem \n",
    "$$\\iiint_V\\left(\\mathbf{\\nabla}\\cdot\\mathbf{F}\\right)\\,dV=\\iint_S\\vec F\\cdot\\vec n\\,dS $$\n",
    "where $\\vec n$ is the normal to $\\partial\\Omega_j$ we get"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$\\iiint_{\\Omega_j}\\frac{\\partial U}{\\partial t}dV+\\iint_{\\partial\\Omega_j}\\vec F(U)\\cdot \\vec n\\,dS=\\iiint_{\\Omega_j}S_U\\,dV$$\n",
    "By using the theorem we actually turned the spatial derivative inside a volume into a surface integral of the function itself. To first order we also suppose that $U$ and $S_U$ are constant inside the volume (this is actually why we discretized our equations) so we get"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "$$\\frac{\\partial U_j}{\\partial t}+\\frac{1}{V_j}\\iint_{\\partial\\Omega_j}\\vec F(U)\\cdot \\vec n\\,dS=S_{U_j}\\tag{4.26}$$\n",
    "In our case, $U$ is $n$, $n\\vec u$ and $\\epsilon$. $\\vec F(U)$ is $n\\vec u$, $n\\vec u\\vec u$ or $\\epsilon\\vec u$.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Hydrodynamics code\n",
    "We are now ready to design a code to handle hydrodynamics flows. Ignoring electric fields and magnetic fields allows us to not only simplify the code but also run the code faster, as we discuss later.\n",
    "\n",
    "We also use [numba](http://numba.pydata.org/) to improve code performance (it is python after all) and some python widget to monitor the remaining time of the computation. \n",
    "\n",
    "Keep in mind that such computation are very intensive on large computers. Using python with neither accelerator (i.e. graphics card) nor parallelization will make any computation inherently slow. So be wise when you choose your resolution.  \n",
    "\n",
    "The code presented here is two-dimensional. It can be used in slab mode, i.e. $z$ is the direction of symmetry, or in cylindrical mode, i.e. $\\phi$ is the direction of symmetry. In other words, in slab geometry any quantity is such that $$U(x,y,z)=U(x,y).$$ In cylindrical geometry we have  $$U(r,\\phi,z)=U(r,z).$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Python housekeeping\n",
    "As usual we import our python libraries. Note the new addition of [ipywidget](https://ipywidgets.readthedocs.io/en/stable/) that may have to be installed using the procedure discussed in Ch01."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "from math import sqrt\n",
    "import matplotlib \n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as colors\n",
    "from numba import jit\n",
    "from ipywidgets.widgets.interaction import show_inline_matplotlib_plots\n",
    "from IPython.display import clear_output\n",
    "from ipywidgets import FloatProgress\n",
    "from IPython.display import display\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Definitions and constants\n",
    "For practical reason we will define some constants that will be use to remember which component in the array correspond to which quantity, e.g. the temperature can be accessed using `tp` at the location `i,j` as `Q[tp,i,j]`. `rh` is the number density, `mx` is the momentum density in the x-direction, `my` and `mz` in the y and z directions. `en` is for the energy density, `tp` the temperature. `nQ` is the total number of variables, from `rh` to `tp`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "rh=0\n",
    "mx=1\n",
    "my=2\n",
    "mz=3\n",
    "en=4\n",
    "tp=5\n",
    "nQ=6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "`mu` is the atomic number of the fluid, in this case aluminum. `aindex` is the adiabatic index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "mu=27.\n",
    "aindex=1.1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Here we define our dimensional parameters. `L0` is the geometrical scale length, `t0` the time scale, `n0` the density scale, `v0` is the velocity scale, `p0` the pressure scale, `te0` the temperature scale.  We also define a couple of floor quantities under which no density, temperature and pressure can go. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "L0=1.0e-3\n",
    "t0=100.0e-9\n",
    "n0=6.0e28\n",
    "v0=L0/t0\n",
    "p0=mu*1.67e-27*n0*v0**2\n",
    "te0=p0/n0/1.6e-19\n",
    "rh_floor = 1.0E-8\n",
    "T_floor = 0.0026/te0\n",
    "rh_mult = 1.1\n",
    "P_floor = rh_floor*T_floor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We now define our geometrical functions. They are used quite often so we will compile them inside the code to accelerate computations. To avoid writing two codes, one for slab symmetry and one for cylindrical symmetry, we wrote this code in for slab symmetry and in Cartesian coordinates, i.e. $(x,y,z)$. When using the code for problem with cylindrical symmetry then $$\\begin{align}\n",
    "&x\\rightarrow r\\\\\n",
    "&y\\rightarrow z\\\\\n",
    "&z\\rightarrow \\phi\\end{align}$$\n",
    "\n",
    "The `rc` function computes the radius in cylindrical coordinates, which appears in source terms and in the conservation equations. Clearly, this is simply $x$ as mentioned above. That's why `rc` returns `xc`. To turn the code into slab symmetry, just have the function `rc` return `1`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "@jit(nopython=True)\n",
    "def xc(i): \n",
    "    return lxd + (i-ngu+1)/dxi\n",
    "\n",
    "@jit(nopython=True)\n",
    "def rc(i):\n",
    "    return xc(i)\n",
    "\n",
    "@jit(nopython=True)\n",
    "def yc(j):\n",
    "    return lyd + (j-ngu+1)/dyi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now add radius and angle function for axi-symmetric distribution in slab geometries, not ot be confused with `rc` above. Note the the letter `c`, for center, is now gone."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "@jit(nopython=True)\n",
    "def r(i,j):\n",
    "    return math.sqrt((xc(i)-(lxd+lxu)/2)**2 + (yc(j)-(lyd+lyu)/2)**2)\n",
    "\n",
    "@jit(nopython=True)\n",
    "def rz(i,j):\n",
    "    return sqrt(xc(i)**2+yc(j)**2)\n",
    "\n",
    "@jit(nopython=True)\n",
    "def theta(i,j):\n",
    "    return math.atan(yc(j)-(lyd+lyu)/2,xc(i)-(lxd+lxu)/2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Finite volume method and time advance algorithms\n",
    "We now compute the sources for all our conservation equations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def get_sources(Qin):\n",
    "    sourcesin=np.zeros((nx,ny,nQ))\n",
    "    for j in range(ngu, ny-ngu):\n",
    "        for i in range(ngu, nx-ngu):\n",
    "\n",
    "            rbp = 0.5*(rc(i+1) + rc(i))\n",
    "            rbm = 0.5*(rc(i) + rc(i-1))\n",
    "\n",
    "            dn = Qin[i,j,rh]\n",
    "            dni=1./dn\n",
    "            vx = Qin[i,j,mx]*dni\n",
    "            vy = Qin[i,j,my]*dni\n",
    "            vz = Qin[i,j,mz]*dni\n",
    "\n",
    "            T = (aindex - 1)*(Qin[i,j,en]*dni - 0.5*(vx**2 + vy**2 + vz**2))\n",
    "            if(T <  T_floor):\n",
    "                T = T_floor\n",
    "            Qin[i,j,tp]=T\n",
    "            sourcesin[i,j,rh] = 0\n",
    "            \n",
    "            P = dn*T\n",
    "\n",
    "            sourcesin[i,j,mx] =  (Qin[i,j,mz]*vz + P)\n",
    "            sourcesin[i,j,mz] =  - Qin[i,j,mz]*vx\n",
    "            sourcesin[i,j,en] = 0\n",
    "    return sourcesin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Here do the time advance of the conservation equations. The flux are used here as seen in Eq. $(4.26)$. The flux are computed later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "@jit(nopython=True)\n",
    "def advance_time_level(Qin,flux_x,flux_y,source):\n",
    "    Qout=np.zeros((nx,ny,nQ))\n",
    "    dxt = dxi*dt\n",
    "    dyt = dyi*dt\n",
    "\n",
    "\n",
    "    for j  in range(ngu, ny-ngu):\n",
    "        for i  in range(ngu, nx-ngu):\n",
    "            rbp = 0.5*(rc(i+1) + rc(i))\n",
    "            rbm = 0.5*(rc(i) + rc(i-1))\n",
    "            rci = 1./rc(i)\n",
    "\n",
    "            Qout[i,j,rh] = Qin[i,j,rh]*rc(i) - dxt*(flux_x[i,j,rh]*rbp-flux_x[i-1,j,rh]*rbm) - dyt*(flux_y[i,j,rh]-flux_y[i,j-1,rh])*rc(i) \n",
    "            Qout[i,j,mx] = Qin[i,j,mx]*rc(i) - dxt*(flux_x[i,j,mx]*rbp-flux_x[i-1,j,mx]*rbm) - dyt*(flux_y[i,j,mx]-flux_y[i,j-1,mx])*rc(i) + dt*source[i,j,mx] \n",
    "            Qout[i,j,my] = Qin[i,j,my]*rc(i) - dxt*(flux_x[i,j,my]*rbp-flux_x[i-1,j,my]*rbm) - dyt*(flux_y[i,j,my]-flux_y[i,j-1,my])*rc(i) + dt*source[i,j,my]\n",
    "            Qout[i,j,mz] = Qin[i,j,mz]*rc(i) - dxt*(flux_x[i,j,mz]*rbp-flux_x[i-1,j,mz]*rbm) - dyt*(flux_y[i,j,mz]-flux_y[i,j-1,mz])*rc(i) + dt*source[i,j,mz]\n",
    "            Qout[i,j,en] = Qin[i,j,en]*rc(i) - dxt*(flux_x[i,j,en]*rbp-flux_x[i-1,j,en]*rbm) - dyt*(flux_y[i,j,en]-flux_y[i,j-1,en])*rc(i) + dt*source[i,j,en]\n",
    "            \n",
    "            Qout[i,j,rh:en+1] = Qout[i,j,rh:en+1]*rci\n",
    "    return Qout"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We now write the function that computes the flux `flx` and the freezing speeds `cfx` along the x-direction. These speeds correspond to the largest speed found in the hyperbolic equation at the given location $(x,y)$. Using freezing speed avoids using a [Riemann solver](https://en.wikipedia.org/wiki/Riemann_solver)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "@jit(nopython=True)\n",
    "def calc_flux_x(Qx):\n",
    "    cfx=np.zeros((nx,nQ))\n",
    "    flx=np.zeros((nx,nQ))\n",
    "\n",
    "    for i in range(0, nx):\n",
    "\n",
    "        dn = Qx[i,rh]\n",
    "        dni = 1./dn\n",
    "        vx = Qx[i,mx]*dni\n",
    "        vy = Qx[i,my]*dni\n",
    "        vz = Qx[i,mz]*dni\n",
    "\n",
    "\n",
    "        P = (aindex - 1)*(Qx[i,en] - 0.5*dn*(vx**2 + vy**2 + vz**2))\n",
    "        if(P < P_floor):\n",
    "            P = P_floor\n",
    "\n",
    "        flx[i,rh] = Qx[i,mx]\n",
    "        flx[i,mx] = Qx[i,mx]*vx + P            \n",
    "        flx[i,my] = Qx[i,my]*vx                       \n",
    "        flx[i,mz] = Qx[i,mz]*vx                                     \n",
    "        flx[i,en] = (Qx[i,en] + P)*vx  \n",
    "\n",
    "\n",
    "        asqr = sqrt(aindex*P*dni)\n",
    "        vf1 = sqrt(vx**2 + aindex*P*dni)\n",
    "\n",
    "        cfx[i,rh] = vf1  \n",
    "        cfx[i,mx] = vf1 \n",
    "        cfx[i,my] = vf1    \n",
    "        cfx[i,mz] = vf1  \n",
    "        cfx[i,en] = vf1 \n",
    "    return cfx,flx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We now write the function that computes the flux `fly` and the freezing speeds `cfy` along the y-direction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "@jit(nopython=True)\n",
    "def calc_flux_y(Qy):\n",
    "    cfy=np.zeros((ny,nQ))\n",
    "    fly=np.zeros((ny,nQ))\n",
    "\n",
    "    for j in range(0, ny):\n",
    "\n",
    "        dn = Qy[j,rh]\n",
    "        dni = 1./dn\n",
    "        vx = Qy[j,mx]*dni\n",
    "        vy = Qy[j,my]*dni \n",
    "        vz = Qy[j,mz]*dni\n",
    "        \n",
    "        P = (aindex - 1)*(Qy[j,en] - 0.5*dn*(vx**2 + vy**2 + vz**2))  \n",
    "        if(P < P_floor):\n",
    "            P = P_floor\n",
    "\n",
    "\n",
    "        fly[j,rh] = Qy[j,my]\n",
    "        fly[j,mx] = Qy[j,mx]*vy                 \n",
    "        fly[j,my] = Qy[j,my]*vy + P              \n",
    "        fly[j,mz] = Qy[j,mz]*vy     \n",
    "        fly[j,en] = (Qy[j,en] + P)*vy\n",
    "\n",
    "        asqr = sqrt(aindex*P*dni)\n",
    "        vf1 = sqrt(vy**2 + aindex*P*dni)\n",
    "\n",
    "        cfy[j,rh] = vf1 \n",
    "        cfy[j,mx] = vf1  \n",
    "        cfy[j,my] = vf1  \n",
    "        cfy[j,mz] = vf1   \n",
    "        cfy[j,en] = vf1  \n",
    "    return cfy,fly"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We now smooth out the different fluxes using a total diminishing variation scheme (or [TVD](https://en.wikipedia.org/wiki/Total_variation_diminishing)]. Basically, this schemes applies numerical viscosity to smooth out sharp transitions caused by shocks or sharp interfaces. Typically, sharp transitions cause numerical oscillations (called [Gibbs phenomenon](https://en.wikipedia.org/wiki/Gibbs_phenomenon)). Note that this scheme is conservative, in the sense that it does conserve all global quantities $n, n\\vec u,\\epsilon$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def tvd2(Qin,n,ff,cfr):   \n",
    "    sl = 1 #use 0.75 for first order\n",
    "    wr = cfr*Qin + ff\n",
    "    wl = cfr*Qin - ff\n",
    "    \n",
    "    fr = wr\n",
    "    fl = np.roll(wl,-1,axis=0)   \n",
    "    \n",
    "    dfrp = np.roll(fr,-1,axis=0) - fr\n",
    "    dfrm = fr - np.roll(fr,+1,axis=0)\n",
    "    dflp = fl - np.roll(fl,-1,axis=0)\n",
    "    dflm = np.roll(fl,+1,axis=0) - fl \n",
    "    dfr=np.zeros((n,nQ))        \n",
    "    dfl=np.zeros((n,nQ))\n",
    "    \n",
    "    flux2 = tvd2_cycle(nQ, n, dfrp, dfrm, dflp, dflm, dfr, dfl, fr, fl, sl)\n",
    "    return flux2\n",
    "\n",
    "@jit(nopython=True)\n",
    "def tvd2_cycle(nQ, n, dfrp, dfrm, dflp, dflm, dfr, dfl, fr, fl, sl):\n",
    "    flux2=np.zeros((n,nQ))\n",
    "    for l in range(nQ):\n",
    "        for i in range(n):\n",
    "            if(dfrp[i,l]*dfrm[i,l] > 0) : \n",
    "                dfr[i,l] = dfrp[i,l]*dfrm[i,l]/(dfrp[i,l] + dfrm[i,l])\n",
    "            else:\n",
    "                dfr[i,l] = 0\n",
    "            if(dflp[i,l]*dflm[i,l] > 0) :\n",
    "                dfl[i,l] = dflp[i,l]*dflm[i,l]/(dflp[i,l] + dflm[i,l])\n",
    "            else:\n",
    "                dfl[i,l] = 0\n",
    "    flux2 = 0.5*(fr - fl + sl*(dfr - dfl))\n",
    "    return flux2\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We truly compute all the fluxes here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def get_flux(Qin):\n",
    "    flux_x=np.zeros((nx,ny,nQ))\n",
    "    flux_y=np.zeros((nx,ny,nQ))\n",
    "    fx=np.zeros((nx,nQ))\n",
    "    cfx=np.zeros((nx,nQ))\n",
    "    ffx=np.zeros((nx,nQ))\n",
    "    fy=np.zeros((ny,nQ))\n",
    "    cfy=np.zeros((ny,nQ))\n",
    "    ffy=np.zeros((ny,nQ))\n",
    "    for j  in range(0, ny):\n",
    "        cfx,ffx=calc_flux_x(Qin[:,j,:])           \n",
    "        flux_x[:,j,:]=tvd2(Qin[:,j,:],nx,ffx,cfx)\n",
    "    for i  in range(0, nx):\n",
    "        cfy,ffy=calc_flux_y( Qin[i,:,:])       \n",
    "        flux_y[i,:,:]=tvd2(Qin[i,:,:],ny,ffy,cfy)\n",
    "    return flux_x,flux_y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We now limit flows to avoid minor instabilities caused by round errors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def limit_flow(Qin):\n",
    "\n",
    "    en_floor = rh_floor*T_floor/(aindex-1)      \n",
    "\n",
    "    for j in range(ngu-1, ny-ngu+1):\n",
    "        for i in range(ngu-1, nx-ngu+1):\n",
    "\n",
    "            if(Qin[i,j,rh]  <=  rh_floor):\n",
    "                Qin[i,j,rh] = rh_floor\n",
    "                Qin[i,j,mx] = 0.0\n",
    "                Qin[i,j,my] = 0.0\n",
    "                Qin[i,j,mz] = 0.0\n",
    "                Qin[i,j,en] = en_floor\n",
    "\n",
    "            if(MMask[i,j]==1):\n",
    "                Qin[i,j,mx] = 0.0\n",
    "                Qin[i,j,my] = 0.0\n",
    "                Qin[i,j,mz] = 0.0 \n",
    "                Qin[i,j,en] = en_floor\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Domain and variable definitions\n",
    "Everything you find below should be the only lines of code you need to change.\n",
    "We now initialize the computational domain. `ngu` correspond to the number of points at the boundary. Leave it alone. `nx` and `ny` are the number of grid points along the x- and y-directions. `lxu` and `lxd` are the upper and lower corners of the mesh along the x-direction. `lyu` and `lyd` are the corners for the y-direction. `dxi` and `dyi` are the inverse of the grid resolution `dx` and `dy`. Since we use both `1/dx` and `/dy` a lot and it is more expansive to compute inverse, we compute them once and that's it. Since python is interactive, we could see them as constants here.\n",
    "\n",
    "**Every time you want to restart a new computation you need to recompile what's below.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "ngu=2\n",
    "nx=45\n",
    "ny=31\n",
    "\n",
    "lxu=15e-3/L0 #note that 15e-3 is in m while 15e-3/L0 is dimensionless\n",
    "lxd=0\n",
    "\n",
    "lyd=0\n",
    "lyu = lyd + (ny-2*ngu)*(lxu-lxd)/(nx-2*ngu)  \n",
    "lyd=-lyu/2. #we do this to center the grid on 0\n",
    "lyu=lyu/2.\n",
    "\n",
    "dxi = (nx-2*ngu)/(lxu-lxd)\n",
    "dyi = (ny-2*ngu)/(lyu-lyd)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "As discussed earlier, it is important to keep the time step `dt` small enough to keep the code stable. For that we use a combination of flow speed and sound speed. There is a stability parameter that is called the [*Courant鈥揊riedrichs鈥揕ewy*](https://en.wikipedia.org/wiki/Courant%E2%80%93Friedrichs%E2%80%93Lewy_condition) condition (or CFL). The fastest speed $U$ in the computation (the maximum of the flow speed and sound speed) defines the largest time step $\\Delta t$ that can be taken as a function of the resolution $\\Delta x$.\n",
    "$$ UC_{CFL}=\\frac{\\Delta x}{\\Delta t}$$\n",
    "$C_{CFL}<1$. Here we take it 0.1 for second order time advance. Note that higher resolution (i.e. $\\Delta x$ smaller) requires to take $\\Delta t$ to be smaller. So every time the resolution is increased by a factor of 2 in both x and y, the computational time is $2^3=8$ times longer.\n",
    "\n",
    "To find the right value for your problem, start with a large number, e.g. 0.5, and decrease that number until the code runs with not error. Then decrease it even more until the final solution of the problem look the same. Then you will have the optimum value for `dt`. When if `cfl` is too small, there are a lot of time steps and sharp features in the solution will start to be washed out. So it is important to find the right `cfl` number. But once it is found then similar problems can be solved using the same condition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_min_dt(Q):\n",
    "    cfl=0.05 #this is where the CFL condition is changed. Keep the rest identical\n",
    "    vmax =sqrt(aindex*1.6e-19*T_floor*te0/(mu*1.6e-27))/v0\n",
    "    for j in range(ny):\n",
    "        for i in range(nx):\n",
    "            dn = Q[i,j,rh]\n",
    "            dni=1./dn\n",
    "            vx = Q[i,j,mx]*dni\n",
    "            vy = Q[i,j,my]*dni\n",
    "            vz = Q[i,j,mz]*dni\n",
    "\n",
    "            T = (aindex - 1)*(Q[i,j,en]*dni - 0.5*(vx**2 + vy**2 + vz**2))\n",
    "            if(T <  T_floor):\n",
    "                T = T_floor\n",
    "            cs=sqrt(aindex*1.6e-19*T*te0/(mu*1.6e-27))/v0\n",
    "            if(vmax < cs  and T > rh_mult*T_floor):\n",
    "                vmax = cs\n",
    "            v = sqrt(vx**2+vy**2+vz**2)\n",
    "            if(vmax < v  and  Q[i,j,rh] > rh_mult*rh_floor):\n",
    "                vmax = v\n",
    "    return min(1./(vmax*dxi),1./(vmax*dyi))*cfl"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Below we defined the initial `ti` and final `tf` times. `n_out` corresponds to to the total number of outputs. The rest are variable initialization. Note the most important one, the time `t`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "ti = 00.0E-2\n",
    "tf = 5.e-6/t0\n",
    "n_out=20\n",
    "\n",
    "n_steps=0\n",
    "t_count=0\n",
    "dt=0.\n",
    "t = ti\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "And now all our arrays are defined here. Note that we use a mask `MMask` for parts of the simulation space were we want to preclude motion. That will come handy later in the course."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "Q=np.zeros((nx,ny,nQ))\n",
    "MMask=np.zeros((nx,ny))\n",
    "Q1=np.copy(Q)\n",
    "Q2=np.copy(Q)\n",
    "sources=np.zeros((nx,ny,nQ))\n",
    "flux_x=np.zeros((nx,ny,nQ))\n",
    "flux_y=np.zeros((nx,ny,nQ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "###  Initial conditions\n",
    "That's for an empty domain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "Q[:,:,rh]=rh_floor\n",
    "Q[:,:,en]=0.026/te0*Q[:,:,rh]/(aindex-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Boundary conditions\n",
    "Below we define our boundary conditions. In this example, we do not use the time `t` and focus only on steady state solutions. The first block define the default boundary conditions for the whole domain. Note that the conditions for the y-direction are pretty simple. These boundary conditions correspond to an open boundary. everything can go through it.\n",
    "\n",
    "Boundary conditions are a bit more complex for the x-direction. We are using a cylindrical coordinate system with open boundary conditions on the right but reflecting boundary conditions on the left. That's because nothing can pass through the axis of symmetry $r=0$.\n",
    "\n",
    "At the end we have the boundary conditions that make up our problem, e.g. material free falling toward the axis of our coordinate system. Note that we are using very large density because the author works in high energy density plasmas. the initial parameters `L0`, `t0` and `n0` can be changed to accommodate other regimes. But, chances are that the CFL scaler `cflm` may have to be adjusted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def set_bc(Qin,t):\n",
    "    if ((rc(0)==rc(1))or(lxd!=0)):\n",
    "        #left open boundary conditions at x=lxu\n",
    "        Qin[1,:,:] = Qin[2,:,:]*rc(2)/rc(1)\n",
    "        Qin[0,:,:] = Qin[1,:,:]*rc(1)/rc(0)\n",
    "    else:\n",
    "        #left reflecting boundary conditions at x=lxd when the symmetry axis is located there\n",
    "        for l in range(ngu):\n",
    "            for k in range(nQ):\n",
    "                if(k == mx):\n",
    "                    Qin[l,:,k] = -Qin[2*ngu-l-1,:,k]\n",
    "                if (k == mz) :\n",
    "                    Qin[l,:,k] = -Qin[2*ngu-l-1,:,k]\n",
    "                if (k == my or k == rh or k == en) :\n",
    "                    Qin[l,:,k] = Qin[2*ngu-l-1,:,k]\n",
    "    #right open boundary conditions at x=lxu\n",
    "    Qin[nx-ngu,:,:] = Qin[nx-ngu-1,:,:]*rc(nx-ngu-1)/rc(nx-ngu)\n",
    "    Qin[nx-ngu+1,:,:] = Qin[nx-ngu,:,:]*rc(nx-ngu)/rc(nx-ngu+1)\n",
    "    #bottom open boundary conditions at y=lyd            \n",
    "    Qin[:,1,:] = Qin[:,2,:]\n",
    "    Qin[:,0,:] = Qin[:,1,:]\n",
    "    #top open boundary conditions at ly=lyu\n",
    "    Qin[:,ny-ngu,:] = Qin[:,ny-ngu-1,:]\n",
    "    Qin[:,ny-ngu+1,:] = Qin[:,ny-ngu,:]\n",
    "    \n",
    "    #our boundary condtions for injecting material radially into our domain\n",
    "    #note that all the values used are dimensionless\n",
    "    N=3           \n",
    "    for j in range (int(ny/2)-N,int(ny/2)+N):\n",
    "        for k in range(ngu):\n",
    "            Q[nx-1-k,j,rh]=6e28/n0\n",
    "            Q[nx-1-k,j,mx]=-4e2/v0*Q[nx-1-k,j,rh]\n",
    "            Q[nx-1-k,j,mz]=-1e2/v0*Q[nx-1-k,j,rh]\n",
    "            Q[nx-1-k,j,en]=0.026/te0*Q[nx-1-k,j,rh]/(aindex-1)+0.5*(Q[nx-1-k,j,mx]**2+Q[nx-1-k,j,my]**2+Q[nx-1-k,j,mz]**2)/Q[nx-1-k,j,rh]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Computation and outputs\n",
    "Let's define some plotting parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "matplotlib.rcParams.update({'font.size': 22})\n",
    "xi = np.linspace(lxd*L0, lxu*L0, nx-2*ngu-1)\n",
    "yi = np.linspace(lyd*L0, lyu*L0, ny-2*ngu-1)\n",
    "progress_bar = FloatProgress(min=ti, max=tf,description='Progress') \n",
    "output_bar = FloatProgress(min=0, max=(tf-ti)/n_out,description='Next output') \n",
    "columns = 2\n",
    "rows = 3\n",
    "box=np.array([lxd,lxu,lyd,lyu])*L0/1e-3\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "And here we go!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
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",
      "text/plain": [
       "<Figure size 2000x1900 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DONE\n"
     ]
    }
   ],
   "source": [
    "while t<tf:\n",
    "    dt=get_min_dt(Q) #compute the optimal dt\n",
    "\n",
    "    set_bc(Q,t) #compute the boundary cnditions\n",
    "    sources=get_sources(Q) #compute the sources\n",
    "    flux_x,flux_y=get_flux(Q) #and ten the fluxes\n",
    "    Q1=advance_time_level(Q,flux_x,flux_y,sources) #advance the solution\n",
    "    limit_flow(Q1) #limit flows that are too fast\n",
    "    \n",
    "    set_bc(Q1,t+dt) #let's do it again\n",
    "    sources=get_sources(Q1)\n",
    "    flux_x,flux_y=get_flux(Q1)\n",
    "    Q2=advance_time_level(Q1,flux_x,flux_y,sources)\n",
    "    limit_flow(Q2)\n",
    "    \n",
    "    Q=0.5*(Q+Q2) #here we do a simple second average\n",
    "    limit_flow(Q)\n",
    "    \n",
    "    n_steps+=1 #time step increased by 1\n",
    "    t_count+=dt #and the time by dt\n",
    "    \n",
    "    progress_bar.value=t #we have defined some progress bars cause python is slow\n",
    "    output_bar.value+=dt # we need to monitor our progress and reduce resolution if it takes too long\n",
    "    \n",
    "    if ((t==ti) or (t_count>(tf-ti)/n_out)): #everything below is plotting....\n",
    "        fig=plt.figure(figsize=(20, 19))\n",
    "        for i in range(1, rows+1):\n",
    "            for j in range(1, columns+1):\n",
    "                k=j+(i-1)*columns\n",
    "                fig.add_subplot(rows, columns, k)\n",
    "                if (k==1):\n",
    "                    data= np.flip(np.transpose(Q[ngu:nx-ngu-1,ngu:ny-ngu-1,rh]*n0),0)\n",
    "                    im = plt.imshow(data, cmap=plt.cm.nipy_spectral, norm=colors.LogNorm(vmin=data.min(), vmax=data.max()),extent=box)\n",
    "                    cb = fig.colorbar(im,fraction=0.046, pad=0.04)\n",
    "                    cb.ax.set_ylabel('$n_i(m^{-3})$', rotation=-90)\n",
    "                if (k==3):\n",
    "                    data=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,mx]**2\n",
    "                    data+=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,my]**2\n",
    "                    data+=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,mz]**2\n",
    "                    data/=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,rh]**2\n",
    "                    data=np.sqrt(data)*L0/t0\n",
    "                    data= np.flip(np.transpose(data),0)\n",
    "                    im = plt.imshow(data, extent=box)\n",
    "                    cb = fig.colorbar(im,fraction=0.046, pad=0.04)\n",
    "                    cb.ax.set_ylabel('$u(m/s)$', rotation=-90)\n",
    "                if (k==2):\n",
    "                    data=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,mx]**2\n",
    "                    data/=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,rh]**2\n",
    "                    data=np.sqrt(data)*L0/t0\n",
    "                    data= np.flip(np.transpose(data),0)\n",
    "                    im = plt.imshow(data, extent=box)\n",
    "                    cb = fig.colorbar(im,fraction=0.046, pad=0.04)\n",
    "                    cb.ax.set_ylabel('$u_r(m/s)$', rotation=-90)\n",
    "                if (k==4):\n",
    "                    data=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,my]**2\n",
    "                    data/=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,rh]**2\n",
    "                    data=np.sqrt(data)*L0/t0\n",
    "                    data= np.flip(np.transpose(data),0)\n",
    "                    im = plt.imshow(data, extent=box)\n",
    "                    cb = fig.colorbar(im,fraction=0.046, pad=0.04)\n",
    "                    cb.ax.set_ylabel('$u_z(m/s)$', rotation=-90)\n",
    "                if (k==6):\n",
    "                    data=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,mz]**2\n",
    "                    data/=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,rh]**2\n",
    "                    data=np.sqrt(data)*L0/t0\n",
    "                    data= np.flip(np.transpose(data),0)\n",
    "                    im = plt.imshow(data, extent=box)\n",
    "                    cb = fig.colorbar(im,fraction=0.046, pad=0.04)\n",
    "                    cb.ax.set_ylabel('$u_\\phi(m/s)$', rotation=-90)\n",
    "                if (k==5):\n",
    "                    data=Q[ngu:nx-ngu-1,ngu:ny-ngu-1,tp]*te0\n",
    "                    data= np.flip(np.transpose(data),0)\n",
    "                    im = plt.imshow(data, cmap=plt.cm.jet,  extent=box)\n",
    "                    cb = fig.colorbar(im,fraction=0.046, pad=0.04)\n",
    "                    cb.ax.set_ylabel('$T(eV)$', rotation=-90)\n",
    "                im.set_interpolation('quadric')\n",
    "                cb.ax.yaxis.set_label_coords(6.5, 0.5)\n",
    "                plt.gca().axes.get_yaxis().set_visible(False)\n",
    "                plt.gca().axes.get_xaxis().set_visible(False)\n",
    "                if (j==1):\n",
    "                    plt.ylabel('z(mm)', rotation=90)\n",
    "                    plt.gca().axes.get_yaxis().set_visible(True)\n",
    "                if (i==rows):\n",
    "                    plt.xlabel('r(mm)', rotation=0)\n",
    "                    plt.gca().axes.get_xaxis().set_visible(True)\n",
    "        plt.tight_layout()\n",
    "        clear_output()\n",
    "        output_bar.value=0\n",
    "        display(progress_bar) # display the bar\n",
    "        display(output_bar) # display the bar\n",
    "        t_count=0\n",
    "        show_inline_matplotlib_plots()\n",
    "    t=t+dt\n",
    "\n",
    "#we are now done. Let's turn off the progress bars.    \n",
    "output_bar.close()\n",
    "del output_bar\n",
    "progress_bar.close()\n",
    "del progress_bar\n",
    "\n",
    "print(\"DONE\")"
   ]
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    "## Problems\n",
    "\n",
    "### Problem 1\n",
    "When a fluid is incompressible, $\\rho(x,y,z,t)=\\rho_0$.  Using the conservation of mass and momentum equations with *no* source of particles show that\n",
    "1. $\\vec\\nabla\\cdot\\vec u=0$\n",
    "2. Also show that\n",
    "$$\\rho_0\\frac{\\partial\\vec u}{\\partial t}+\\rho_0\\big(\\vec u\\cdot \\nabla\\big)\\vec u=-\\vec\\nabla p$$\n",
    "\n",
    "\n",
    "### Problem 2\n",
    "\n",
    "1. Using a version of `Debye_length_check` from HW04, write a new function that evolves particles in time. In this function, the electric field of all particles is computed on a square mesh. Then the function uses the closest mesh points of any particles to compute the local electric field felt by the particle, using some sort of interpolation (e.g. bilinear). Once the field at each particle location is known, the function \"pushes\" all the particles in time using a first order scheme. \n",
    "2. Using this function, plot the time average electric field for a plasma where $n_i=n_e=10^{13}cm^{-3}$, $Z_i=1$ and $T_e=0.2eV$.\n",
    "\n",
    "NB: If you can make it work, then you just wrote a particle in cell (or PIC) code!\n",
    "\n",
    "### Problem 3\n",
    "Using the fluid code as given in Ch04, generate a new plot which gives the Mach number $M_A$ of the flow at all time steps. If the flow is subsonic then $M_A<1$. If the flow is supersonic then $M_A>1$. The Mach number is given by $$M_A=\\frac{u}{c_s}$$ where $u$ is the flow speed and $c_s$ is the ion sound speed given by $c_s=\\sqrt{\\gamma e T_e/m_i}$. Do do this \n",
    "1. Use the definitions and create a new variable which contains the Mach number at all time steps. Beware of using the right $m_i$\n",
    "2. Once computed, plot the Mach number across the whole domain, together with on the output plots.\n",
    "3. Do you see any supersonic regions?\n",
    "\n",
    "### Problem 4\n",
    "Again using the code provided in Ch04, create a diverging flow at the right boundary with an opening angle of $5^o$ above the midplane and again $-5^o$ below the midplane with total velocity 500m/s. In this case, can you found if a jet forms on axis?\n",
    "\n",
    "### Problem 5\n",
    "Turn the fluid code of Ch04 into a code with periodic boundary conditions for all quantities at the top and bottom of the grid (i.e. y=lyu and y=lyd).\n"
   ]
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   "source": [
    "漏 Pierre Gourdain, The University of Rochester, Charlie Seyler, Cornell University, 2020"
   ]
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